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Keynote talk by Dr. Jean-Luc Gaudiot: Fighting Amdahl's law in many-core and GPU parallel architectures with value prediction

机译:Jean-Luc Gaudiot博士的主题演讲:在许多核心和GPU并行架构中争夺Amdahl的法律,具有价值预测

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The newly emerging many-core-on-a-chip designs have renewed an intense interest in parallel processing. By applying Amdahl's formulation to the programs in the PARSEC and SPLASH-2 benchmark suites, we find that most applications may not have sufficient parallelism to efficiently utilize modern parallel machines. The long sequential portions in these application programs are caused by computation as well as communication latency. However, value prediction techniques may allow the “parallelization” of the sequential portion by predicting values before they are produced. In conventional superscalar architectures, the computation latency dominates the sequential sections. Thus value prediction techniques may be used to predict the computation result before it is produced. In many-core architectures, since the communication latency increases with the number of cores, value prediction techniques may be used to reduce both the communication and computation latency. We extend these ideas by using GPUs to accelerate programs that contain limited parallelism and those that are hard to parallelize.
机译:新兴的许多芯片芯片设计已经更新了并行处理的强烈兴趣。通过将Amdahl的配方应用于Parsec和Splash-2基准套房的方案,我们发现大多数应用可能没有足够的并行性,以有效地利用现代的平行机器。这些应用程序中的长期部分是由计算和通信延迟引起的。然而,通过在产生它们之前通过预测值来允许序列部分的“并行化”。在传统的超卡架构中,计算延迟主导顺序部分。因此,值预测技术可以用于预测在产生之前的计算结果。在许多核心架构中,由于通信延迟随着核的数量而增加,因此可以使用值预测技术来减少通信和计算延迟。我们通过使用GPU来加速包含有限并行度的程序来扩展这些想法以及那些难以并行化的程序。

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